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Grounds the interview character in the ingested corpus while she stays in-voice. Tier-3 agents are tool-less by design in v1, so this is the consumer-side workaround (DEC-6, worldtree-dev ruling): per opted-in interview turn, ratatoskr consults Mimir out-of-band, extracts the passages, and pins them as memory_context on the character's turn. She frames the pinned corpus as her own memory. - src/ratatoskr/kb_bridge.py (new, RETIRE-READY): pin_kb_context — THE single seam (INV-KB-1). Allowlist-gated (INV-KB-4: ratatoskr:donut only), hard-timeout-bounded, degrades to [] on any failure/timeout/empty (INV-KB-3, never raises; CancelledError propagates). Imports nothing from the SDK-adapter / TTS core. aclosing() closes the SDK stream deterministically on the DoneEvent break. - wt.stream_turn: memory_context passthrough (defaults None — inert for every other caller and for the bridge's own retirement). Seam-review catch: the contract's original touch list undercounted wt.py by one file (recorded in the contract). - web/server.py: TurnHandle.agent_id + the single pin_kb_context call-site on the turn path; the browser now sends agent_id so the allowlist can gate. - web/static/index.html: the turn POST carries agent_id. Consult prompt tuned live: "search_library EXACTLY ONCE, no read_note" converges Mimir in ~3-15s (the softer "do one search" phrasing looped past 25s on conversational questions). TDD: 12 kb_bridge unit tests + wt memory_context forwarding + 2 server wiring tests (531 green). Live-smoked on :8081/b128: pin_kb_context grounds in the DCC corpus (real excerpts, <20s) and Donut answers in-voice; degrades cleanly on a slow consult. KNOWN LIMIT surfaced (not a bridge defect): DCC's fiction index is weak (failed backfill, a worldtree-dev item), so grounding is opportunistic — the bridge's real payoff is a corpus the model does not already know. Per docs/contracts/donut_voiced_interview.contract.md (slice 3 of 3).
Ratatoskr
A Worldtree Conversation API debug console. Runs up and down Worldtree's API surface — sessions, turns, persona, tools, admin events, Bifrost state — carrying messages between layers. Like the squirrel.
The product is the observability surface; chat is the input mechanism.
Devs run Ratatoskr against a local Worldtree to watch a turn flow through
every layer of the system, side-by-side. The interactive surface is the
web console (ratatoskr-web); a headless --send CLI drives scripted smokes.
Status
v0 scaffold. Design locked; implementation hasn't started. The dev team owns the implementation pass.
Read in this order
docs/design-brief.md— the locked design. Read this first. Every architectural decision is recorded with its rationale, the alternatives considered, and (where relevant) the operator's lock-in moment.docs/SPEC-PIN.md— what Worldtree spec version Ratatoskr is built against, where the vendored snapshot lives, and how to bump the pin.docs/conversation-api-spec.md— the vendored Worldtree spec snapshot. Read this to understand the API surface Ratatoskr consumes. Do not import anything from a Worldtree checkout — the boundary is the spec, not the code. Seedocs/design-brief.md§2.CLAUDE.md— Claude Code conventions for this repo (mostly inherited from the Corviduo template).persistent-memory.md— durable intent across context resets. Update as decisions and state evolve.
Quickstart
# 1. Environment
uv venv && source .venv/bin/activate
uv pip install -e ".[dev]"
# 2. Verify the spec pin
cat docs/SPEC-PIN.md # documented Worldtree SHA + bump procedure
# 3. Tests (none yet; scaffold only)
uv run pytest
# 4. Run against a local Worldtree (Worldtree must be running)
# Interactive web console:
ratatoskr-web --host 0.0.0.0 --port 8765
# Headless CLI (scripted smoke):
ratatoskr --send "hello" --new --agent mimir --api-key "$WORLDTREE_API_KEY"
What this repo is NOT
- NOT a polished consumer for Worldtree's end-users — that's the web app.
- NOT a Worldtree admin tool — admin CLI is separate (
sessions_cli.pylives in Worldtree). - NOT a featuretracking shadow of the web app — when the Conversation API surface grows, Ratatoskr does not necessarily grow with it.
- NOT a remote-Worldtree debug client — file-tail surfaces (persona log, server log) assume local-dev posture.
The full negative-clause list lives in docs/design-brief.md §6.
Boundary rule
Ratatoskr depends on a small, fixed surface:
httpx+httpx-sse(network layer)starlette+uvicorn(the web console; thewebextra)- Worldtree's published Conversation API spec at the pinned SHA
Hard rule: no imports from a Worldtree checkout. No core.* imports,
no from worldtree.*, no shared models, no submodule of Worldtree. The
spec is the entire surface. Boundary smoke test at tests/test_no_worldtree_imports.py
enforces this in CI.
Version-skew strategy
The dev team is decoupled from Worldtree's dev team. To detect drift when Worldtree changes the API:
- Spec-version pin in
pyproject.toml(worldtree-spec-rev). Bump explicitly; bumps are a tracked action. - Recorded-SSE snapshot tests at
tests/snapshots/. Captured against a live Worldtree; replayed in CI. Re-record after every pin bump. - Conformance smoke test — boots Worldtree via Docker compose in CI, runs a one-turn happy path. Catches integration-level drift.
See docs/SPEC-PIN.md for the bump procedure.
Consumer-side discoveries
If you find a spec gap, ambiguity, or missing-but-needed endpoint while working on Ratatoskr: route the discovery back to worldtree-dev via althing rather than via PR on Worldtree directly. The separate-team boundary is intentional and helps catch spec gaps that an in-tree consumer would paper over.
Related repos
- Worldtree — the API Ratatoskr consumes
- brokkr-smithy — authored this design brief
- Skaldsong — another Worldtree API consumer (Python; render-and-aggregate pattern)
- mead-hall — another Worldtree API consumer (TypeScript; server-side broker)